The present disclosure relates generally to non-invasive measurement of physiological parameters and, more particularly, to multi-wavelength photon density wave measurements of physiological parameters.
This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
Pulse oximetry may be defined as a non-invasive technique that facilitates monitoring of a patient's blood flow characteristics. For example, pulse oximetry may be used to measure blood oxygen saturation of hemoglobin in a patient's arterial blood and/or the patient's heart rate. Specifically, these blood flow characteristic measurements may be acquired using a non-invasive sensor that passes light through a portion of a patient's tissue and photo-electrically senses the absorption and scattering of the light through the tissue. Typical pulse oximetry technology may employ two light emitting diodes (LEDs) and a single optical detector to measure pulse and oxygen saturation of a given tissue bed.
A typical signal resulting from the sensed light may be referred to as a plethysmograph waveform. Such measurements are largely based on absorption of emitted light by specific types of blood constituents. Once acquired, this measurement may be used with various algorithms to estimate a relative amount of blood constituent in the tissue. For example, such measurements may provide a ratio of oxygenated hemoglobin to total hemoglobin in the volume being monitored. The amount of arterial blood in the tissue is generally time-varying during a cardiac cycle, which is reflected in the plethysmographic waveform.
The accuracy of blood flow characteristic estimation via pulse oximetry may depend on a number of factors. For example, variations in light absorption characteristics can affect accuracy depending on where the sensor is located and/or the physiology of the patient being monitored. Additionally, various types of noise and interference can create inaccuracies. For example, electrical noise, physiological noise, and other interference can contribute to inaccurate blood flow characteristic estimates.